Ch 12 and13 Flashcards
Descriptive and inferential stats for bivariate and multivariate cases
Parametric statistics
Built in assumptions about distribution (like normal distribution, etc)
Non-parametric statistics
No assumptions
Frequency distribution
raw or relative cumulative distribution
Central tendency
Measure of the middle
Dispersion
Measure of spread
Nominal descriptive stats
Mode and variation ratio
Ordinal descriptive stats
Median and range
Interval/ratio descriptive stats
Mean and standard deviation
Z scores
express how far a given value is away from the mean through standard deviations
Types of claims
Descriptive, differences, relationship, causal effect
Type I error
H0 incorrectly rejected
Type II error
Fail to reject H0
Recoding variables
Reinterpreting them for use in statistical analysis
weakness of p value
doesnt account for size of data set or importance of relationship
Input into R of N/A cases
should specify to exclude; inserted as ±99 and will skew data
Dummy variables
Representing nominal or ordinal categories as arbitrary values
Mann-Whitney U
Compares based on ranking subgroups within data set and then seeing if the match
Nominal-nominal inferential stats
Chi squared
Ordinal - nominal/ordinal inferential stats
Chi squared, mann whitney U
I/R (nonnormal)-nominal, ordinal, I/R inferential stats
Mann whitney U
I/R (normal) - nominal, ordinal inferential stats
ANOVA, difference of means
I/R (normal)-I/R (normal) inferential stats
t-test, F-test
F ratio
calculates statistical significance of r^2
ANOVA
comparing difference of means across more than 2 groups
